Staff Data Engineer (AWS, Java & Real-Time Data)

Staff Data Engineer (AWS, Java & Real-Time Data)

• Lead the design and delivery of a new cloud-based credit risk data domain.

• Shape data models, streaming solutions and engineering standards from the ground up.

• Build with AWS, Java and modern real-time data technologies as CommBank transforms its technology estate.

Do Work That Matters

Be part of the team driving enterprise-wide transformation at CommBank. Corporate Technology delivers the modern platforms, enterprise data and critical systems that power the Bank’s Operations and Corporate functions. You’ll collaborate across diverse teams, solve complex technology challenges and help shape the future of one of Australia’s leading organisations.

As a Staff Data Engineer in the Credit Risk Profile Squad, you’ll provide hands-on technical leadership as we establish a new service domain. You’ll design the data foundations, build secure and resilient pipelines, and enable trusted credit risk information to be accessed through data products, real-time events and APIs.

See yourself in our team

The Credit Risk Profile Squad is a new team focused on modernising legacy credit risk assets and creating a scalable, cloud-based system of record. The squad will support real-time event notifications, reusable data products and future AI-enabled capabilities while progressively transitioning consumers from legacy systems.

In this role, you will:

• Lead the design of conceptual, logical and physical data models for the new Credit Risk Profile service domain.

• Design, build and operate batch and near real-time ingestion and data-processing pipelines using Java, AWS and distributed processing technologies.

• Establish engineering standards, reusable patterns, architectural guardrails and technical decisions across the squad.

• Develop trusted data products with appropriate quality controls, metadata, lineage, access controls and governance.

• Guide the migration of data and consumers from legacy assets to modern cloud-based services.

• Build automated testing, continuous delivery, monitoring and observability into the full engineering lifecycle.

• Influence technical decisions across engineering, architecture and product teams, balancing delivery, resilience, security and cost.

• Mentor engineers and contribute to an inclusive culture of engineering excellence, learning and continuous improvement.

We’re interested in hearing from people who:

You are an experienced data engineering leader who can move between strategy, design and hands-on delivery. You enjoy solving complex data problems and can provide clear technical direction while helping other engineers grow.

We know strong candidates may not have worked with every technology below. If you have deep experience in modern data engineering and real-time processing, we would still like to hear from you.

• Bring strong Java engineering capability for building production-grade data ingestion, event-streaming and processing solutions.

• Have experience designing and delivering data solutions on AWS, including technologies such as Glue Catalog, S3, Iceberg, Kinesis, MSK or Kafka, Lambda and PostgreSQL.

• Understand real-time data concepts such as change data capture, event-driven ingestion, windowing, checkpointing, schema evolution, replay and operational recovery.

• Have strong data modelling and database capability, including SQL, partitioning, stored procedures and conceptual, logical and physical modelling.

• Have experience with Apache Flink, or strong transferable experience with Spark Streaming or another distributed stream-processing framework.

• Apply sound engineering practices across GitHub Actions, CI/CD, automated testing, DevSecOps and source control.

• Design for production reliability using monitoring, logging, alerting and observability platforms such as CloudWatch, Grafana, Splunk, Datadog or similar.

• Can set technical direction, influence stakeholders and mentor engineers working across complex programs or initiatives.

• Experience with Python, Parquet, data replication, data quality, enterprise semantic models or regulated data environments will also be valued. 

• Relevant AWS or data engineering certifications are welcome but are not essential where you can demonstrate equivalent practical experience.

Working with us:

At CommBank, we're committed to creating an accessible, inclusive and respectful workplace. If you require support or adjustments, please let us know. We welcome applications from people of all backgrounds and we're particularly committed to making a positive difference for Aboriginal and/or Torres Strait Islander Peoples. For support please contact 1800 989 696.

If this opportunity excites you, we’d love to hear from you. Apply today.